Mentoring schemes are increasingly being encouraged by companies, and the once manual selection process is being superseded by more accurate innovations in technology.
Mentoring is widely recognised as highly beneficial to professionals in industries across the board. HR directors and L&D managers regularly turn to mentoring to improve employee engagement, learning and even employee retention.
Mentoring is on the increase and organisations are looking to offer solid, scalable mentoring schemes. Frustratingly, though, mentoring is traditionally a resource-heavy, manual, labourious and often complicated process.
Technology is beginning to come onto the scene to dramatically improve mentoring accessibility, effectiveness and even the reporting of mentoring success.
It’s this resource that often has limited mentoring to those individuals that organisations define as ‘most in need’: either the ‘top talent’ and managers or those struggling at the bottom of an organisation.
Fortunately, technology is beginning to come onto the scene to dramatically improve mentoring accessibility, effectiveness and even the reporting of mentoring success. But what exactly are the existing challenges, what can these new technologies do and most importantly, do they work?
Finding the perfect match
Mentor matching is where most mentoring programmes and relationships begin. A fairly straightforward concept: a mentor and a mentee are matched, based on experience, insight and requirements.
This sounds easy when you think about a handful of mentors and a handful of mentees. The problem is that once you have more than 15 mentors and mentees, the process can start to become wholly unsatisfactory.
Now consider a company with thousands of employees - it simply is not possible. Like a lot of things, mentoring will end up being put onto an excel spreadsheet, become an unmanageable mess and end up taking over an HR director or L&D director’s life.
Oudated systems need an overhaul
I’ve been fortunate enough to work closely with HR and L&D managers in a wide-range of industries over the past year, and my favourite conversation occurred when I asked a mentor manager of a prestigious UK university how they managed their mentor matching.
I soon realised that mentor matching was a real issue for a lot of people and organisations.
Her response blew me away. She told me that they printed off the applications of every university student requesting a mentor and then printed off the profiles of all the mentors on their books, laid them out across the library floor and then went through them, pairing them as best they could.
I was shocked when I heard this, but I soon realised that mentor matching was a real issue for a lot of people and organisations. With the growth of artificial intelligence, software solutions and data science, matching no longer needs to be manual. It is with these new technologies and online platforms that we can resolve the first issue: mentor matching.
If you’re sceptical about the effectiveness of automated mentor matching, that is entirely understandable. Anyone who can convince you that automated mentor matching will be 100% effective is kidding themselves. That being said, with huge advances is matching algorithms, data science and machine learning, it can be extremely powerful and often comes close to total accuracy.
These technologies and platforms can help to make mentor matching pain-free, what about the challenges around keeping mentor engagement levels sustained?
In some instances, it is likely to be even better than a manual match where individuals who are charged with the responsibility of scanning through profiles could miss out on certain profile factors.
Now these technologies and platforms can help to make mentor matching pain-free, what about the challenges around keeping mentor engagement levels sustained? It used to fall to mentor managers to send ‘nudge’ emails out, reminding employees and mentoring members to arrange their monthly mentor meetings, setup their goal and agenda setting and to stay on top of their mentor relationships.
Fortunately, the same technology that can help to automate the mentor matching also exists to intelligently remind individuals about their mentors and mentees - sending helpful reminders about goals, tasks, meetings and more. No longer do HR directors have to be on the backs of employees and members in mentoring programmes - the automation handles it.
Return on investment
The final and often most tricky aspect to mentoring is the reporting that organisations so often crave. For an organisation to prove worth, they need data to back it up and without data there are likely to be fewer budget allocations and ultimately learning and development programmes will be cut.
The problem here is that mentoring is seen in so many different ways and each organisation has a different view of what mentoring is and how it should be conducted. What most mentoring programme managers do agree on is that mentoring is informal.
By its very nature, mentoring expectations and requirements are often set by the mentor and mentee. Adding formal structure, process and learnings to a mentoring relationship can quickly turn it into coaching and training - this is not mentoring.
Mentors act as guides and support posts; a mentee can turn to them when faced with a workplace challenge, needing more general advice on career progression, industry experience and additional support areas.
So, how does an organisation capture this data and turn it into measurable success insights? Well, mentoring programmes and technologies out there can help individuals to add goals and targets to their own mentoring relationship, as well as allowing assigned mentors to add additional goals and schedule in meetings.
67% of people with a mentor stayed with the organisation for three years longer than those who didn’t.
This technology allows organisations to report on goals setup vs goals completed and meetings scheduled in. The same technologies also support mentor rating and feedback systems, which in turn can feed additional reporting data into company directors and managers.
Finally, data based on employee retention can be fed into these programmes, in order to see mentoring effectiveness. An example here would be: 67% of people with a mentor stayed with the organisation for three years longer than those who didn’t.
With the increase of mentoring programmes and the rise of technological solutions, how are you using them to help your organisation? If you aren’t yet doing so, perhaps you should consider using mentoring platforms and technology to scale up your offering to employees.